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DeepSeek-V3.2-Speciale vs Parse

Comparing DeepSeek-V3.2-Speciale and Parse across benchmarks, pricing, and capabilities.

DeepSeek · Cohere · Updated for 2026

Which is better?

DeepSeek-V3.2-Speciale and Parse trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

DeepSeek-V3.2-Speciale also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V3.2-Speciale

  • you process long inputs — it offers a 131,072 token context window
  • you need open weights you can self-host or fine-tune

Choose Parse

  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.28 / M
— / M
Output price
$0.42 / M
— / M
Context window
131,072
8,192

Individual benchmarks

8 reported for DeepSeek-V3.2-Speciale · 1 for Parse

No common benchmarks found

DeepSeek-V3.2-Speciale and Parsedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

682.7B diff

DeepSeek-V3.2-Speciale has 682.7B more parameters than Parse, making it 29682.6% larger.

DeepSeek
DeepSeek-V3.2-Speciale
685.0Bparameters
Cohere
Parse
2.3Bparameters
685.0B
DeepSeek-V3.2-Speciale
2.3B
Parse

Context Window

Maximum input and output token capacity

DeepSeek-V3.2-Speciale accepts 131,072 input tokens compared to Parse's 8,192 tokens. Only DeepSeek-V3.2-Speciale specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3.2-Speciale
Input131,072 tokens
Output131,072 tokens
Cohere
Parse
Input8,192 tokens
Output- tokens
Mon Sep 07 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Parse supports multimodal inputs, whereas DeepSeek-V3.2-Speciale does not.

Parse can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.2-Speciale

Text
Images
Audio
Video

Parse

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2-Speciale is licensed under MIT, while Parse uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V3.2-Speciale

MIT

Open weights

Parse

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2-Speciale was released on 2025-12-01, while Parse was released on 2026-08-27.

Parse is 9 months newer than DeepSeek-V3.2-Speciale.

DeepSeek-V3.2-Speciale

Dec 1, 2025

9 months ago

Parse

Aug 27, 2026

1 weeks ago

8mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-V3.2-Speciale is available from DeepSeek. Parse is available from Azure, Cohere.

DeepSeek-V3.2-Speciale

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

Parse

azure logo
Azure
cohere logo
Cohere
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-V3.2-Speciale and Parse side-by-side, then vote on the output you prefer.

DeepSeek-V3.2-Speciale
✓ Preferred
Parse
Open in Playground

FAQ

Common questions about DeepSeek-V3.2-Speciale vs Parse.

Which is better, DeepSeek-V3.2-Speciale or Parse?

DeepSeek-V3.2-Speciale (DeepSeek) and Parse (Cohere) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-V3.2-Speciale compare to Parse in benchmarks?

DeepSeek-V3.2-Speciale scores HMMT 2025: 99.2%, AIME 2025: 96.0%, CodeForces: 90.0%, t2-bench: 80.3%, SWE-Bench Verified: 73.1%. Parse scores ParseBench: 79.2%.

What are the context window sizes for DeepSeek-V3.2-Speciale and Parse?

DeepSeek-V3.2-Speciale supports 131K tokens and Parse supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3.2-Speciale and Parse?

Key differences include context window (131K vs 8K), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2-Speciale and Parse?

DeepSeek-V3.2-Speciale is developed by DeepSeek and Parse is developed by Cohere.